IDEAS home Printed from https://ideas.repec.org/f/pbl241.html
   My authors  Follow this author

Mårten Blix
(Marten Blix)

Personal Details

First Name:Marten
Middle Name:
Last Name:Blix
Suffix:
RePEc Short-ID:pbl241
http://www.martenblix.com

Affiliation

Institutet för Näringslivsforskning (IFN)

Stockholm, Sweden
http://www.ifn.se/
RePEc:edi:iuiiise (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Books

Working papers

  1. Blix, Mårten, 2020. "Money for Nothin’ – Digitalization and Fluid Tax Bases," Working Paper Series 1316, Research Institute of Industrial Economics.
  2. Blix, Mårten & Jeansson, Johanna, 2018. "Telemedicine and the Welfare State: The Swedish Experience," Working Paper Series 1238, Research Institute of Industrial Economics.
  3. Mårten Blix, 2017. "Structural Change and the Freight Transport Labour Market," International Transport Forum Discussion Papers 2017/12, OECD Publishing.
  4. Blix, Mårten & Sellin, Peter, 2000. "A Bivariate Distribution for Inflation and Output Forecasts," Working Paper Series 102, Sveriges Riksbank (Central Bank of Sweden).
  5. Blix, Mårten, 1999. "Forecasting Swedish Inflation With a Markov Switching VAR," Working Paper Series 76, Sveriges Riksbank (Central Bank of Sweden).
  6. Blix, M, 1997. "Rational Expectations in a VAR with Markov Switching," Papers 627, Stockholm - International Economic Studies.

Articles

  1. Mårten Blix, 2017. "The Effects of Digitalisation on Labour Market Polarisation and Tax Revenue," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 18(04), pages 09-14, December.

Books

  1. Mårten Blix, 2017. "Digitalization, Immigration and the Welfare State," Books, Edward Elgar Publishing, number 17438.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Blix, Mårten, 2020. "Money for Nothin’ – Digitalization and Fluid Tax Bases," Working Paper Series 1316, Research Institute of Industrial Economics.

    Cited by:

    1. Yu Song & Chenfei Qian & Susan Pickard, 2021. "Age-Related Digital Divide during the COVID-19 Pandemic in China," IJERPH, MDPI, vol. 18(21), pages 1-13, October.

  2. Blix, Mårten & Jeansson, Johanna, 2018. "Telemedicine and the Welfare State: The Swedish Experience," Working Paper Series 1238, Research Institute of Industrial Economics.

    Cited by:

    1. Ziebland, Sue & Hyde, Emma & Powell, John, 2021. "Power, paradox and pessimism: On the unintended consequences of digital health technologies in primary care," Social Science & Medicine, Elsevier, vol. 289(C).

  3. Blix, Mårten & Sellin, Peter, 2000. "A Bivariate Distribution for Inflation and Output Forecasts," Working Paper Series 102, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Maximiano Pinheiro & Paulo Esteves, 2012. "On the uncertainty and risks of macroeconomic forecasts: combining judgements with sample and model information," Empirical Economics, Springer, vol. 42(3), pages 639-665, June.
    2. Villani, Mattias & Larsson, Rolf, 2004. "The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis," Working Paper Series 175, Sveriges Riksbank (Central Bank of Sweden).
    3. Virmani, Vineet, 2004. "Fan Charts as Useful ‘Maps’ for an Inflation-Targeting Central Bank: An Illustration of the Sveriges Riksbank’s Method for Presenting Density Forecasts of Inflation," IIMA Working Papers WP2004-04-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    4. Berg, Claes & Jansson, Per & Vredin, Anders, 2004. "How Useful are Simple Rules for Monetary Policy? The Swedish Experience," Working Paper Series 169, Sveriges Riksbank (Central Bank of Sweden).
    5. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    6. Ali Al‐Nowaihi & Livio Stracca, 2003. "Behavioural Central Bank Loss Functions, Skewed Risks and Certainty Equivalence," Manchester School, University of Manchester, vol. 71(s1), pages 21-38, September.

  4. Blix, Mårten, 1999. "Forecasting Swedish Inflation With a Markov Switching VAR," Working Paper Series 76, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Barnett, William & Park, Sohee, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," MPRA Paper 110298, University Library of Munich, Germany.
    3. Lawrence Christiano & Mathias Trabandt & Karl Walentin, 2021. "Involuntary Unemployment and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 39, pages 26-54, January.
    4. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    5. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    6. Maehashi, Kohei & Shintani, Mototsugu, 2020. "Macroeconomic forecasting using factor models and machine learning: an application to Japan," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
    7. Choi, Jin Ho & Suh, Sangwon, 2021. "A filtered currency carry trade," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    8. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    9. Mohsen Khezri & Seyed Ehsan Hosseinidoust & Mohammad Kazem Naziri, 2019. "Investigating the Temporary and Permanent Influential Variables on Iran Inflation Using TVP-DMA Models," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 23(1), pages 209-234, Winter.
    10. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2021. "Spurious relationships in high-dimensional systems with strong or mild persistence," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1480-1497.
    11. Bo Zhang & Jamie Cross & Na Guo, 2020. "Time-Varying Trend Models for Forecasting Inflation in Australia," Working Papers No 09/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    12. Timmermann, Allan & Pettenuzzo, Davide & Gargano, Antonio, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," CEPR Discussion Papers 10104, C.E.P.R. Discussion Papers.
    13. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    14. Constantinescu, Mihnea & Nguyen, Anh Dinh Minh, 2021. "A century of gaps: Untangling business cycles from secular trends," Economic Modelling, Elsevier, vol. 100(C).
    15. Quast, Josefine & Wolters, Maik H., 2019. "Reliable Real-time Output Gap Estimates Based on a Modified Hamilton Filter," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203535, Verein für Socialpolitik / German Economic Association.
    16. Binh Thai Pham & Hector Sala, 2022. "The implications of public expenditures on a small economy in transition: a Bayesian DSGE approach," Economic Change and Restructuring, Springer, vol. 55(1), pages 401-431, February.
    17. Elmar Mertens & James M. Nason, 2020. "Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility," Quantitative Economics, Econometric Society, vol. 11(4), pages 1485-1520, November.
    18. Gantert, Konstantin, 2022. "The impact of active aggregate demand on utilisation-adjusted TFP," IWH Discussion Papers 9/2022, Halle Institute for Economic Research (IWH).
    19. Eser, Fabian & Karadi, Peter & Lane, Philip R. & Moretti, Laura & Osbat, Chiara, 2020. "The Phillips Curve at the ECB," Working Paper Series 2400, European Central Bank.
    20. Vincent Dropsy & Nathalie Grand, 2004. "Exchange Rate and Inflation Targeting in Morocco and Tunisia," Working Papers 0421, Economic Research Forum, revised 10 2004.
    21. John Cotter & Emmanuel Eyiah-Donkor & Valerio Potì, 2023. "Commodity futures return predictability and intertemporal asset pricing," Post-Print hal-04192933, HAL.
    22. Lopez-Buenache, German, 2019. "The evolution of monetary policy effectiveness under macroeconomic instability," Economic Modelling, Elsevier, vol. 83(C), pages 221-233.
    23. Bourioune, Tahar & Chiad, Faycal, 2022. "Estimation de l’IPC par les modèles non paramétriques : cas de l’Algérie [CPI estimation by non parametric models: case of Algeria]," MPRA Paper 113783, University Library of Munich, Germany, revised 2022.
    24. Akgun, Oguzhan & Pirotte, Alain & Urga, Giovanni, 2020. "Forecasting using heterogeneous panels with cross-sectional dependence," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1211-1227.
    25. Bertrand Achou & Hippolyte d'Albis & Eleni Iliopulo, 2021. "House prices and rents: a reappraisal," Cahiers de recherche / Working Papers 6, Institut sur la retraite et l'épargne / Retirement and Savings Institute.
    26. Bhaghoe, Sailesh & Ooft, Gavin, 2021. "Nowcasting Quarterly GDP Growth in Suriname with Factor-MIDAS and Mixed-Frequency VAR Models," Studies in Applied Economics 176, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
    27. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    28. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
    29. Paloviita, Maritta & Mayes, David, 2005. "The use of real-time information in Phillips-curve relationships for the euro area," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 415-434, December.
    30. Zhihong Chen & Azhar Iqbal & Huiwen Lai, 2011. "Forecasting the probability of US recessions: a Probit and dynamic factor modelling approach," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 44(2), pages 651-672, May.
    31. Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 869-889, August.
    32. Fasanya, Ismail O. & Awodimila, Crystal P., 2020. "Are commodity prices good predictors of inflation? The African perspective," Resources Policy, Elsevier, vol. 69(C).
    33. Kaloyan Ganev, 2020. "Real-Time vs. Full-Sample Performance of One-Sided and Two-Sided HP Filters. An Application to 27 EU Member States’ GDP Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(3), pages 251-272, September.
    34. Bertrand Achou & Hippolyte d'Albis & Eleni Iliopulos, 2021. "Real Estate and Rental Markets during Covid Times," Working Papers halshs-03231807, HAL.
    35. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    36. Peter C. B. Phillips & Sainan Jin, 2021. "Business Cycles, Trend Elimination, And The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 469-520, May.
    37. W. Scott Frame & Nika Lazaryan & Ping McLemore & Atanas Mihov, 2022. "Operational Loss Recoveries and the Macroeconomic Environment: Evidence from the U.S. Banking Sector," Working Papers 2215, Federal Reserve Bank of Dallas.
    38. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    39. Lingfeng Li, 2003. "Macroeconomic Factors and the Correlation of Stock and Bond Returns," Yale School of Management Working Papers ysm328, Yale School of Management.
    40. Bhattacharya, Rudrani & Kapoor, Mrigankshi, 2020. "Forecasting Consumer Price Index Inflation in India: Vector Error Correction Mechanism Vs. Dynamic Factor Model Approach for Non-Stationary Time Series," Working Papers 20/323, National Institute of Public Finance and Policy.
    41. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    42. Niko Hauzenberger & Daniel Kaufmann & Rebecca Stuart & Cédric Tille, 2022. "What Drives Long-Term Interest Rates? Evidence from the Entire Swiss Franc History 1852-2020," IRENE Working Papers 22-03, IRENE Institute of Economic Research.
    43. Muellbauer, John, 2018. "The Future of Macroeconomics," INET Oxford Working Papers 2018-10, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    44. Le Ha Thu & Roberto Leon-Gonzalez, 2021. "Forecasting Macroeconomic Variables in Emerging Economies: An Application to Vietnam," GRIPS Discussion Papers 21-03, National Graduate Institute for Policy Studies.
    45. Clements, Michael P. & Reade, J. James, 2020. "Forecasting and forecast narratives: The Bank of England Inflation Reports," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1488-1500.
    46. Adriana Cornea‐Madeira & João Madeira, 2022. "Econometric Analysis of Switching Expectations in UK Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 651-673, June.
    47. Han, Liyan & Jin, Jiayu & Wu, Lei & Zeng, Hongchao, 2020. "The volatility linkage between energy and agricultural futures markets with external shocks," International Review of Financial Analysis, Elsevier, vol. 68(C).
    48. In Choi & Hanbat Jeong, 2020. "Differencing versus nondifferencing in factor‐based forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 728-750, September.
    49. Amélie Charles & Olivier Darné, 0. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 0, pages 1-24.
    50. Na Guo & Bo Zhang & Jamie L. Cross, 2022. "Time‐varying trend models for forecasting inflation in Australia," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 316-330, March.
    51. Ooft, G. & Bhaghoe, S. & Franses, Ph.H.B.F., 2019. "Forecasting Annual Inflation in Suriname," Econometric Institute Research Papers EI2019-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    52. Pham, Binh T. & Sala, Hector & Silva, José I., 2018. "Growth and real business cycles in Vietnam and the ASEAN-5. Does the trend shock matter?," MPRA Paper 90297, University Library of Munich, Germany.
    53. Francis In & Sangbae Kim, 2012. "An Introduction to Wavelet Theory in Finance:A Wavelet Multiscale Approach," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8431, August.
    54. Donadelli, Michael & Jüppner, Marcus & Prosperi, Lorenzo, 2019. "Risk weighting, private lending and macroeconomic dynamics," Discussion Papers 30/2019, Deutsche Bundesbank.
    55. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    56. Mili, Mehdi & Sahut, Jean-Michel & Teulon, Frédéric, 2012. "Non linear and asymmetric linkages between real growth in the Euro area and global financial market conditions: New evidence," Economic Modelling, Elsevier, vol. 29(3), pages 734-741.
    57. Koffi, Siméon, 2022. "Prévision de l’inflation en Côte D’ivoire : Analyse Comparée des Modèles Arima, Holt-Winters, et Lstm [Inflation Forecasting in Côte D'Ivoire: A Comparative Analysis of the Arima, Holt-Winters, and," MPRA Paper 113961, University Library of Munich, Germany.
    58. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.
    59. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    60. Josué Diwambuena & Raquel Fonseca & Stefan Schubert, 2021. "Italian Labour Frictions and Wage Rigidities in an Estimated DSGE," CIRANO Working Papers 2021s-33, CIRANO.
    61. Davidson, James, 2004. "Forecasting Markov-switching dynamic, conditionally heteroscedastic processes," Statistics & Probability Letters, Elsevier, vol. 68(2), pages 137-147, June.
    62. Heather D. Gibson & Stephen G. Hall & George S. Tavlas, 2020. "A Suggestion for a Dynamic Multi Factor Model (DMFM)," Working Papers 282, Bank of Greece.
    63. Anna Staszewska-Bystrova & Victor Bystrov, 2022. "The Evolution of Fiscal Policy and Public Debt Dynamics: The Case of Sweden," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 67-83.
    64. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    65. Jan Prüser, 2021. "Forecasting US inflation using Markov dimension switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 481-499, April.
    66. Mehmet Ezer, 2019. "Do Monetary Aggregates Belong In A Monetary Model? Evidence From The Uk," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 509-530, December.
    67. Roccazzella, Francesco & Candelon, Bertrand, 2022. "Should we care about ECB inflation expectations?," LIDAM Discussion Papers LFIN 2022004, Université catholique de Louvain, Louvain Finance (LFIN).
    68. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    69. Andrejs Bessonovs & Olegs Krasnopjorovs, 2020. "Short-Term Inflation Projections Model and Its Assessment in Latvia," Working Papers 2020/01, Latvijas Banka.
    70. Doina Chichernea & Kershen Huang & Alex Petkevich, 2019. "Does maturity matter? The case of treasury futures volume," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(10), pages 1301-1321, October.
    71. Kate Ivory & Eddie Casey & Niall Conroy, 2020. "Ireland’s Fiscal Spending Multipliers," The Economic and Social Review, Economic and Social Studies, vol. 51(1), pages 133-172.
    72. Afees A. Salisu & Raymond Swaray & Hadiza Sa'id, 2021. "Improving forecasting accuracy of the Phillips curve in OECD countries: The role of commodity prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2946-2975, April.
    73. Jane Ihrig & Jaime Marquez, 2004. "An Empirical Analysis of Inflation in OECD Countries," International Finance, Wiley Blackwell, vol. 7(1), pages 61-84, March.
    74. Jonas Dovern & Christopher Zuber, 2020. "Recessions and Potential Output: Disentangling Measurement Errors, Supply Shocks, and Hysteresis Effects," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(4), pages 1431-1466, October.
    75. Grand Nathalie & Dropsy Vincent, 2005. "Exchange Rate And Inflation Targeting In Morocco And Tunisia," Macroeconomics 0507018, University Library of Munich, Germany.
    76. Gantert, Konstantin, 2022. "The Impact of Active Aggregate Demand on Utilization-Adjusted TFP," VfS Annual Conference 2022 (Basel): Big Data in Economics 264103, Verein für Socialpolitik / German Economic Association.
    77. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    78. Gianluca Laganà & Andrew Mountford, 2005. "Measuring Monetary Policy In The Uk: A Factor‐Augmented Vector Autoregression Model Approach," Manchester School, University of Manchester, vol. 73(s1), pages 77-98, September.
    79. Oyenyinka Sunday Omoshoro‐Jones & Lumengo Bonga‐Bonga, 2022. "Intra‐regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model," The World Economy, Wiley Blackwell, vol. 45(1), pages 251-275, January.
    80. Sung Won Seo & Suk Joon Byun & Jun Sik Kim, 2020. "Index options open interest and stock market returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(6), pages 989-1010, June.
    81. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    82. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    83. Luca Brugnolini & Giuseppe Ragusa, 2022. "Euro Area Deflationary Pressure Index," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 883-900, October.
    84. Roberto Casarin & Stefano Grassi & Francesco Ravazzollo & Herman K. van Dijk, 2019. "Forecast Density Combinations with Dynamic Learning for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers 19-025/III, Tinbergen Institute.
    85. Eddie Casey, 2019. "Inside the "Upside Down": Estimating Ireland's Output Gap," The Economic and Social Review, Economic and Social Studies, vol. 50(1), pages 5-34.
    86. Barbara Roffia & Andrea Zaghini, 2008. "Excess money growth and inflation dynamics," Temi di discussione (Economic working papers) 657, Bank of Italy, Economic Research and International Relations Area.
    87. Thu, Le Ha & Leon-Gonzalez, Roberto, 2021. "Forecasting macroeconomic variables in emerging economies," Journal of Asian Economics, Elsevier, vol. 77(C).
    88. Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
    89. Kevin S. Nell, 2006. "Structural Change And Nonlinearities In A Phillips Curve Model For South Africa," Contemporary Economic Policy, Western Economic Association International, vol. 24(4), pages 600-617, October.
    90. Jean-michel Sahut & Medhi Mili & Frédéric Teulon, 2012. "What is the linkage between real growth in the Euro area and global financial market conditions?," Economics Bulletin, AccessEcon, vol. 32(3), pages 2464-2480.
    91. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    92. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    93. Solikin M. Juhro & Bernard Njindan Iyke, 2019. "Forecasting Indonesian Inflation Within An Inflation-Targeting Framework: Do Large-Scale Models Pay Off?," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 423-436, December.
    94. Ibrahim L. Awad, 2019. "Revisiting the Exchange Rate Pass-Through to Domestic Inflation in Egypt: Why Is the Statistical Association Weak in the Short Run?," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 18(1), pages 59-77, June.
    95. Khemiri, Rim & Ali, Mohamed Sami Ben, 2013. "Exchange rate pass-through and inflation dynamics in Tunisia: A Markov-switching approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-30.
    96. Anthoulla Phella, 2020. "Consistent Specification Test of the Quantile Autoregression," Papers 2010.03898, arXiv.org, revised Jan 2024.
    97. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2021. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Tinbergen Institute Discussion Papers 21-016/III, Tinbergen Institute.
    98. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
    99. Kimolo, Deogratius, 2009. "Modelling and Forecasting Inflation in Tanzania: A Univariate Time Series Analysis," MPRA Paper 114782, University Library of Munich, Germany.
    100. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    101. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
    102. James H. James & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," Working Papers 2005-2, Princeton University. Economics Department..
    103. Julie K. Smith, 2005. "Inflation targeting and core inflation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 38(3), pages 1018-1036, August.
    104. Savas Papadopoulos & Pantelis Stavroulias & Thomas Sager, 2019. "Systemic early warning systems for EU14 based on the 2008 crisis: proposed estimation and model assessment for classification forecasting," Journal of Banking Regulation, Palgrave Macmillan, vol. 20(3), pages 226-244, September.
    105. Huiwen Lai & Eric C. Y. Ng, 2020. "On business cycle forecasting," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-26, December.
    106. Khan, Zeeshan & Hussain, Muzzammil & Shahbaz, Muhammad & Yang, Siqun & Jiao, Zhilun, 2020. "Natural resource abundance, technological innovation, and human capital nexus with financial development: A case study of China," Resources Policy, Elsevier, vol. 65(C).
    107. Aparicio, Diego & Bertolotto, Manuel I., 2020. "Forecasting inflation with online prices," International Journal of Forecasting, Elsevier, vol. 36(2), pages 232-247.
    108. Garegnani, Lorena & Gómez Aguirre, Maximiliano, 2018. "Forecasting Inflation in Argentina," IDB Publications (Working Papers) 8940, Inter-American Development Bank.
    109. Wolf, Elias & Mokinski, Frieder & Schüler, Yves, 2020. "On adjusting the one-sided Hodrick-Prescott filter," Discussion Papers 11/2020, Deutsche Bundesbank.

  5. Blix, M, 1997. "Rational Expectations in a VAR with Markov Switching," Papers 627, Stockholm - International Economic Studies.

    Cited by:

    1. Arielle Beyaert & Juan Jose Perez-Castejon, 2009. "Markov-switching models, rational expectations and the term structure of interest rates," Applied Economics, Taylor & Francis Journals, vol. 41(3), pages 399-412.
    2. Nicolas Rautureau, 2004. "Modèles à changement de régime et test de la théorie des anticipations rationnelles de la structure par terme des taux dintérêt en France," Économie et Prévision, Programme National Persée, vol. 163(2), pages 117-129.
    3. Matthieu Droumaguet & Anders Warne & Tomasz Wozniak, 2015. "Granger Causality and Regime Inference in Bayesian Markov-Switching VARs," Department of Economics - Working Papers Series 1191, The University of Melbourne.
    4. Beyaert, Arielle & Garcia-Solanes, Jose & Perez-Castejon, Juan J., 2007. "Uncovered interest parity with switching regimes," Economic Modelling, Elsevier, vol. 24(2), pages 189-202, March.

Articles

  1. Mårten Blix, 2017. "The Effects of Digitalisation on Labour Market Polarisation and Tax Revenue," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 18(04), pages 09-14, December.

    Cited by:

    1. Giulia Parola, 2020. "Escape from parents? basement? Post COVID-19 scenarios for the future of youth employment in Italy," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 2020(111), pages 51-71.
    2. Martin Lakomý, 2023. "Effects of digital skills and other individual factors on retirement decision-making and their gender differences," European Journal of Ageing, Springer, vol. 20(1), pages 1-12, December.
    3. , Aisdl, 2018. "The role of gender on the effects of Indonesian manpower skills on their competition readiness/preparedness," OSF Preprints hvyg8, Center for Open Science.

Books

    Sorry, no citations of books recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CBA: Central Banking (2) 2001-10-16 2001-12-26
  2. NEP-ETS: Econometric Time Series (2) 2001-10-16 2001-12-26
  3. NEP-MON: Monetary Economics (2) 2001-10-16 2001-12-26
  4. NEP-ICT: Information and Communication Technologies (1) 2020-02-17
  5. NEP-PAY: Payment Systems and Financial Technology (1) 2020-02-17
  6. NEP-PBE: Public Economics (1) 2020-02-17
  7. NEP-PUB: Public Finance (1) 2020-02-17

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Marten Blix
(Marten Blix) should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.